[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間:2025-09-04 (世界標準時間)。"],[],[],null,["# Interpret prediction results from text sentiment analysis models\n\n| Starting on September 15, 2024, you can only customize classification, entity extraction, and sentiment analysis objectives by moving to Vertex AI Gemini prompts and tuning. Training or updating models for Vertex AI AutoML for Text classification, entity extraction, and sentiment analysis objectives will no longer be available. You can continue using existing Vertex AI AutoML Text models until June 15, 2025. For a comparison of AutoML text and Gemini, see [Gemini for AutoML text users](/vertex-ai/docs/start/automl-gemini-comparison). For more information about how Gemini offers enhanced user experience through improved prompting capabilities, see [Introduction to tuning](/vertex-ai/generative-ai/docs/models/tune-gemini-overview). To get started with tuning, see [Model tuning for Gemini text models](/vertex-ai/generative-ai/docs/models/tune_gemini/tune-gemini-learn)\n\nAfter requesting a prediction, Vertex AI returns results based on your\nmodel's objective. Predictions from sentiment analysis models return the overall\nsentiment for a document. The sentiment is represented by an integer from 0 to\nthe model's max sentiment score, which can be equal to or less than 10. The\nmaximum sentiment value for a model is set during training. For example, if a\nmodel was trained on a dataset with a maximum sentiment score of 2, predicted\nsentiment scores can be 0 (negative), 1 (neutral), or 2 (positive).\n\nExample batch prediction output\n-------------------------------\n\nThe following sample is the predicted result for a single document. Because the\nmodel's maximum sentiment score is 8, the predicted sentiment for this sample is\nclearly positive.\n\n\n| **Note**: The following JSON Lines example includes line breaks for\n| readability. In your JSON Lines files, line breaks are included only after each\n| each JSON object.\n\n\u003cbr /\u003e\n\n\n```\n{\n \"instance\": {\"content\": \"gs://bucket/text.txt\", \"mimeType\": \"text/plain\"},\n \"prediction\": {\"sentiment\": 8}\n}\n```"]]